Determining a pixon map for image reconstruction

A method for determining a pixon map entry for a first pixon kernel function of a set of pixon kernel functions having different sizes, the method comprising:

• receiving a data set;
• receiving an input object associated to the data;
• smoothing the input object based on the first pixon kernel function, thereby creating a smoothed object;
• determining a delta object by subtracting the input object from the smoothed object;
• determining a delta data model by projecting the delta object from object space into data space;
• determining statistical data factors by evaluating the delta data model using the data and a Mighell-like statistical weight;
• determining statistical object factors by back-projecting the statistical data factors from data space into object space;
• multiplying the entries of the delta object by the corresponding statistical object factors, thereby creating a statistical object;
• determining an object point for which a value of the statistical object at the object point has transitioned from being outside the limitation of a pre-set cut-off value to being inside the limitation;
• selecting the next smaller pixon kernel function compared to the first pixon kernel function to contribute to an entry of the pixon map corresponding to the object point.

A non-transitory computer readable medium having included software thereon, the software including instructions to determine a pixon map for pixon smoothing, the instructions comprising:

• receiving the data set;
• receiving an input object associated to the data set;
• determining, in a series of steps, statistical objects for a set of pixon kernel functions, wherein each step includes
• selecting a pixon kernel function from the set of pixon kernel functions,
• smoothing the input object on the basis of the selected pixon kernel function, thereby creating a smoothed object, and
• determining the statistical object for the selected pixon kernel function on the basis of the smoothed object, the data set, and a Mighell-like statistical weight;
• determining contributions of the pixon kernel functions to the pixon map based on the statistical objects;
• and
• assigning values to the pixon map corresponding to the contributions of the pixon kernel functions.